Overview

Dataset statistics

Number of variables14
Number of observations30425
Missing cells40565
Missing cells (%)9.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 MiB
Average record size in memory112.0 B

Variable types

Numeric5
Text2
Unsupported3
DateTime2
Categorical2

Alerts

Local Currency has constant value ""Constant
Unit Price is highly overall correlated with Total PO Value and 1 other fieldsHigh correlation
Total PO Value is highly overall correlated with Unit Price and 1 other fieldsHigh correlation
Total PO Value Local Currency is highly overall correlated with Unit Price and 1 other fieldsHigh correlation
PO Order Date has 20277 (66.6%) missing valuesMissing
PO Approval Date has 20267 (66.6%) missing valuesMissing
Unit Price is highly skewed (γ1 = 60.78282175)Skewed
Total PO Value is highly skewed (γ1 = 60.56316997)Skewed
Total PO Value Local Currency is highly skewed (γ1 = 60.56316997)Skewed
PO Identifier is uniformly distributedUniform
PO Identifier has unique valuesUnique
PO Number is an unsupported type, check if it needs cleaning or further analysisUnsupported
Item is an unsupported type, check if it needs cleaning or further analysisUnsupported
Description is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unit Price has 728 (2.4%) zerosZeros
Total PO Value has 728 (2.4%) zerosZeros
Total PO Value Local Currency has 728 (2.4%) zerosZeros

Reproduction

Analysis started2023-05-30 04:08:32.870470
Analysis finished2023-05-30 04:16:50.897891
Duration8 minutes and 18.03 seconds
Software versionydata-profiling vv4.2.0
Download configurationconfig.json

Variables

PO Identifier
Real number (ℝ)

UNIFORM  UNIQUE 

Distinct30425
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15213
Minimum1
Maximum30425
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size237.8 KiB
2023-05-30T12:16:51.022827image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1522.2
Q17607
median15213
Q322819
95-th percentile28903.8
Maximum30425
Range30424
Interquartile range (IQR)15212

Descriptive statistics

Standard deviation8783.0853
Coefficient of variation (CV)0.57734078
Kurtosis-1.2
Mean15213
Median Absolute Deviation (MAD)7606
Skewness0
Sum4.6285552 × 108
Variance77142588
MonotonicityNot monotonic
2023-05-30T12:16:51.194693image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
768 1
 
< 0.1%
20274 1
 
< 0.1%
20286 1
 
< 0.1%
20285 1
 
< 0.1%
20284 1
 
< 0.1%
20283 1
 
< 0.1%
20282 1
 
< 0.1%
20281 1
 
< 0.1%
20280 1
 
< 0.1%
20279 1
 
< 0.1%
Other values (30415) 30415
> 99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
30425 1
< 0.1%
30424 1
< 0.1%
30423 1
< 0.1%
30422 1
< 0.1%
30421 1
< 0.1%
30420 1
< 0.1%
30419 1
< 0.1%
30418 1
< 0.1%
30417 1
< 0.1%
30416 1
< 0.1%

Vendor Number
Real number (ℝ)

Distinct6591
Distinct (%)21.7%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean797562.21
Minimum0
Maximum1796774
Zeros129
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size237.8 KiB
2023-05-30T12:16:51.366529image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7708
Q129677
median1008971
Q31249060
95-th percentile1749198.4
Maximum1796774
Range1796774
Interquartile range (IQR)1219383

Descriptive statistics

Standard deviation669363.93
Coefficient of variation (CV)0.83926234
Kurtosis-1.5096421
Mean797562.21
Median Absolute Deviation (MAD)735273
Skewness-0.016852322
Sum2.4265033 × 1010
Variance4.4804806 × 1011
MonotonicityNot monotonic
2023-05-30T12:16:51.538368image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1065902 825
 
2.7%
1001584 649
 
2.1%
1249060 541
 
1.8%
1087660 539
 
1.8%
36519 538
 
1.8%
1008361 459
 
1.5%
1000709 409
 
1.3%
12341 354
 
1.2%
11527 298
 
1.0%
1018638 291
 
1.0%
Other values (6581) 25521
83.9%
ValueCountFrequency (%)
0 129
0.4%
39 22
 
0.1%
45 1
 
< 0.1%
61 15
 
< 0.1%
89 2
 
< 0.1%
124 3
 
< 0.1%
143 2
 
< 0.1%
148 2
 
< 0.1%
210 1
 
< 0.1%
278 32
 
0.1%
ValueCountFrequency (%)
1796774 1
 
< 0.1%
1796486 3
 
< 0.1%
1793589 6
< 0.1%
1792944 2
 
< 0.1%
1792325 11
< 0.1%
1791874 1
 
< 0.1%
1791711 1
 
< 0.1%
1791481 1
 
< 0.1%
1791364 1
 
< 0.1%
1791228 1
 
< 0.1%
Distinct2235
Distinct (%)7.3%
Missing2
Missing (%)< 0.1%
Memory size237.8 KiB
2023-05-30T12:16:51.850796image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length78
Median length66
Mean length23.461164
Min length3

Characters and Unicode

Total characters713759
Distinct characters73
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)3.3%

Sample

1st rowExLibris
2nd rowExLibris
3rd rowAlliant Insurance Services, Inc
4th rowAlliant Insurance Services, Inc
5th rowEMC
ValueCountFrequency (%)
inc 11324
 
11.9%
technology 6525
 
6.9%
group 6351
 
6.7%
integration 5909
 
6.2%
business 5262
 
5.5%
products 4630
 
4.9%
smile 4073
 
4.3%
solutions 2218
 
2.3%
corporation 1801
 
1.9%
systems 1540
 
1.6%
Other values (2424) 45201
47.7%
2023-05-30T12:16:52.366296image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
64428
 
9.0%
o 50450
 
7.1%
n 49778
 
7.0%
e 45842
 
6.4%
t 36405
 
5.1%
r 33915
 
4.8%
s 33688
 
4.7%
i 32698
 
4.6%
c 27630
 
3.9%
I 25862
 
3.6%
Other values (63) 313063
43.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 456306
63.9%
Uppercase Letter 176635
 
24.7%
Space Separator 64428
 
9.0%
Other Punctuation 14967
 
2.1%
Decimal Number 406
 
0.1%
Open Punctuation 376
 
0.1%
Close Punctuation 371
 
0.1%
Dash Punctuation 269
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 50450
11.1%
n 49778
10.9%
e 45842
10.0%
t 36405
 
8.0%
r 33915
 
7.4%
s 33688
 
7.4%
i 32698
 
7.2%
c 27630
 
6.1%
u 23265
 
5.1%
a 21863
 
4.8%
Other values (16) 100772
22.1%
Uppercase Letter
ValueCountFrequency (%)
I 25862
14.6%
S 19541
11.1%
T 16857
 
9.5%
C 13595
 
7.7%
N 10118
 
5.7%
E 9849
 
5.6%
G 8842
 
5.0%
P 8744
 
5.0%
B 8608
 
4.9%
A 8498
 
4.8%
Other values (16) 46121
26.1%
Decimal Number
ValueCountFrequency (%)
3 271
66.7%
1 64
 
15.8%
2 27
 
6.7%
0 16
 
3.9%
4 12
 
3.0%
5 9
 
2.2%
7 4
 
1.0%
6 2
 
0.5%
9 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 8752
58.5%
. 4177
27.9%
& 996
 
6.7%
/ 696
 
4.7%
' 344
 
2.3%
: 1
 
< 0.1%
@ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
64428
100.0%
Open Punctuation
ValueCountFrequency (%)
( 376
100.0%
Close Punctuation
ValueCountFrequency (%)
) 371
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 269
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 632941
88.7%
Common 80818
 
11.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 50450
 
8.0%
n 49778
 
7.9%
e 45842
 
7.2%
t 36405
 
5.8%
r 33915
 
5.4%
s 33688
 
5.3%
i 32698
 
5.2%
c 27630
 
4.4%
I 25862
 
4.1%
u 23265
 
3.7%
Other values (42) 273408
43.2%
Common
ValueCountFrequency (%)
64428
79.7%
, 8752
 
10.8%
. 4177
 
5.2%
& 996
 
1.2%
/ 696
 
0.9%
( 376
 
0.5%
) 371
 
0.5%
' 344
 
0.4%
3 271
 
0.3%
- 269
 
0.3%
Other values (11) 138
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 713759
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64428
 
9.0%
o 50450
 
7.1%
n 49778
 
7.0%
e 45842
 
6.4%
t 36405
 
5.1%
r 33915
 
4.8%
s 33688
 
4.7%
i 32698
 
4.6%
c 27630
 
3.9%
I 25862
 
3.6%
Other values (63) 313063
43.9%

PO Number
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size237.8 KiB
Distinct26110
Distinct (%)85.8%
Missing0
Missing (%)0.0%
Memory size237.8 KiB
2023-05-30T12:16:52.647484image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length26
Median length24
Mean length13.272145
Min length6

Characters and Unicode

Total characters403805
Distinct characters53
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23237 ?
Unique (%)76.4%

Sample

1st rowDenise Rivers
2nd rowDenise Rivers
3rd rowDenise Rivers
4th rowDenise Rivers
5th rowDenise Rivers
ValueCountFrequency (%)
michael 696
 
1.1%
smith 634
 
1.0%
johnson 544
 
0.9%
james 526
 
0.8%
david 470
 
0.8%
jennifer 465
 
0.7%
williams 427
 
0.7%
john 426
 
0.7%
thomas 412
 
0.7%
christopher 403
 
0.6%
Other values (1585) 57240
92.0%
2023-05-30T12:16:53.107487image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 37578
 
9.3%
a 37073
 
9.2%
31818
 
7.9%
n 30358
 
7.5%
r 29219
 
7.2%
i 24537
 
6.1%
o 21867
 
5.4%
l 20465
 
5.1%
s 18236
 
4.5%
t 14111
 
3.5%
Other values (43) 138543
34.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 308083
76.3%
Uppercase Letter 63268
 
15.7%
Space Separator 31818
 
7.9%
Other Punctuation 636
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 37578
12.2%
a 37073
12.0%
n 30358
9.9%
r 29219
9.5%
i 24537
8.0%
o 21867
 
7.1%
l 20465
 
6.6%
s 18236
 
5.9%
t 14111
 
4.6%
h 13377
 
4.3%
Other values (16) 61262
19.9%
Uppercase Letter
ValueCountFrequency (%)
M 7332
11.6%
J 6139
 
9.7%
S 5103
 
8.1%
C 4701
 
7.4%
D 4305
 
6.8%
A 3890
 
6.1%
B 3882
 
6.1%
R 3833
 
6.1%
H 2985
 
4.7%
W 2964
 
4.7%
Other values (15) 18134
28.7%
Space Separator
ValueCountFrequency (%)
31818
100.0%
Other Punctuation
ValueCountFrequency (%)
. 636
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 371351
92.0%
Common 32454
 
8.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 37578
 
10.1%
a 37073
 
10.0%
n 30358
 
8.2%
r 29219
 
7.9%
i 24537
 
6.6%
o 21867
 
5.9%
l 20465
 
5.5%
s 18236
 
4.9%
t 14111
 
3.8%
h 13377
 
3.6%
Other values (41) 124530
33.5%
Common
ValueCountFrequency (%)
31818
98.0%
. 636
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 403805
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 37578
 
9.3%
a 37073
 
9.2%
31818
 
7.9%
n 30358
 
7.5%
r 29219
 
7.2%
i 24537
 
6.1%
o 21867
 
5.4%
l 20465
 
5.1%
s 18236
 
4.5%
t 14111
 
3.5%
Other values (43) 138543
34.3%
Distinct451
Distinct (%)4.4%
Missing20277
Missing (%)66.6%
Memory size237.8 KiB
Minimum1913-10-10 00:00:00
Maximum2021-06-06 00:00:00
2023-05-30T12:16:53.279318image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:16:53.451154image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct459
Distinct (%)4.5%
Missing20267
Missing (%)66.6%
Memory size237.8 KiB
Minimum1913-10-10 00:00:00
Maximum2021-06-06 00:00:00
2023-05-30T12:16:53.622953image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:16:53.779200image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Item
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)< 0.1%
Memory size237.8 KiB

Description
Unsupported

REJECTED  UNSUPPORTED 

Missing16
Missing (%)0.1%
Memory size237.8 KiB

Unit Price
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct15131
Distinct (%)49.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50891.452
Minimum-195915.9
Maximum97106933
Zeros728
Zeros (%)2.4%
Negative76
Negative (%)0.2%
Memory size237.8 KiB
2023-05-30T12:16:53.966624image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-195915.9
5-th percentile8.55
Q1113
median575.83
Q37255
95-th percentile96810.028
Maximum97106933
Range97302849
Interquartile range (IQR)7142

Descriptive statistics

Standard deviation1047316.7
Coefficient of variation (CV)20.579422
Kurtosis4358.746
Mean50891.452
Median Absolute Deviation (MAD)565.83
Skewness60.782822
Sum1.5483724 × 109
Variance1.0968722 × 1012
MonotonicityNot monotonic
2023-05-30T12:16:54.138490image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 728
 
2.4%
105 234
 
0.8%
245 176
 
0.6%
198.07 171
 
0.6%
150 127
 
0.4%
113 119
 
0.4%
103.25 118
 
0.4%
252.76 117
 
0.4%
3712.4 116
 
0.4%
121.33 103
 
0.3%
Other values (15121) 28416
93.4%
ValueCountFrequency (%)
-195915.9 1
< 0.1%
-55529 1
< 0.1%
-44606.57 1
< 0.1%
-36626.88 1
< 0.1%
-30000 1
< 0.1%
-16750 2
< 0.1%
-14674.49 1
< 0.1%
-11651 1
< 0.1%
-8732 1
< 0.1%
-7980 1
< 0.1%
ValueCountFrequency (%)
97106933.19 1
< 0.1%
73982622 1
< 0.1%
62482622 1
< 0.1%
54000000 1
< 0.1%
52419751 1
< 0.1%
44072001 1
< 0.1%
40649810 1
< 0.1%
39500000 1
< 0.1%
28420574 1
< 0.1%
16145096 1
< 0.1%

Total PO Value
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct17475
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53750.226
Minimum-195915.9
Maximum97106933
Zeros728
Zeros (%)2.4%
Negative76
Negative (%)0.2%
Memory size237.8 KiB
2023-05-30T12:16:54.310327image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-195915.9
5-th percentile32
Q1362.1
median1980.7
Q310000
95-th percentile107065.3
Maximum97106933
Range97302849
Interquartile range (IQR)9637.9

Descriptive statistics

Standard deviation1048605.7
Coefficient of variation (CV)19.508862
Kurtosis4336.7462
Mean53750.226
Median Absolute Deviation (MAD)1908.71
Skewness60.56317
Sum1.6353506 × 109
Variance1.099574 × 1012
MonotonicityNot monotonic
2023-05-30T12:16:54.482164image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 728
 
2.4%
105 193
 
0.6%
150 131
 
0.4%
252.76 105
 
0.3%
3712.4 102
 
0.3%
4095 89
 
0.3%
368 75
 
0.2%
5003.26 71
 
0.2%
534.01 69
 
0.2%
1620 67
 
0.2%
Other values (17465) 28795
94.6%
ValueCountFrequency (%)
-195915.9 1
< 0.1%
-55529 1
< 0.1%
-44606.57 1
< 0.1%
-36626.88 1
< 0.1%
-30000 1
< 0.1%
-25600 1
< 0.1%
-16750 2
< 0.1%
-14674.49 1
< 0.1%
-13562 1
< 0.1%
-11651 1
< 0.1%
ValueCountFrequency (%)
97106933.19 1
< 0.1%
73982622 1
< 0.1%
62482622 1
< 0.1%
54000000 1
< 0.1%
52419751 1
< 0.1%
44072001 1
< 0.1%
40649810 1
< 0.1%
39500000 1
< 0.1%
28420574 1
< 0.1%
16145096 1
< 0.1%

Local Currency
Categorical

Distinct1
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size237.8 KiB
SGD
30424 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters91272
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSGD
2nd rowSGD
3rd rowSGD
4th rowSGD
5th rowSGD

Common Values

ValueCountFrequency (%)
SGD 30424
> 99.9%
(Missing) 1
 
< 0.1%

Length

2023-05-30T12:16:54.638374image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-05-30T12:16:54.794589image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
sgd 30424
100.0%

Most occurring characters

ValueCountFrequency (%)
S 30424
33.3%
G 30424
33.3%
D 30424
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 91272
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 30424
33.3%
G 30424
33.3%
D 30424
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 91272
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 30424
33.3%
G 30424
33.3%
D 30424
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 91272
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 30424
33.3%
G 30424
33.3%
D 30424
33.3%

Total PO Value Local Currency
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct17475
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53750.226
Minimum-195915.9
Maximum97106933
Zeros728
Zeros (%)2.4%
Negative76
Negative (%)0.2%
Memory size237.8 KiB
2023-05-30T12:16:54.935179image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-195915.9
5-th percentile32
Q1362.1
median1980.7
Q310000
95-th percentile107065.3
Maximum97106933
Range97302849
Interquartile range (IQR)9637.9

Descriptive statistics

Standard deviation1048605.7
Coefficient of variation (CV)19.508862
Kurtosis4336.7462
Mean53750.226
Median Absolute Deviation (MAD)1908.71
Skewness60.56317
Sum1.6353506 × 109
Variance1.099574 × 1012
MonotonicityNot monotonic
2023-05-30T12:16:55.107018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 728
 
2.4%
105 193
 
0.6%
150 131
 
0.4%
252.76 105
 
0.3%
3712.4 102
 
0.3%
4095 89
 
0.3%
368 75
 
0.2%
5003.26 71
 
0.2%
534.01 69
 
0.2%
1620 67
 
0.2%
Other values (17465) 28795
94.6%
ValueCountFrequency (%)
-195915.9 1
< 0.1%
-55529 1
< 0.1%
-44606.57 1
< 0.1%
-36626.88 1
< 0.1%
-30000 1
< 0.1%
-25600 1
< 0.1%
-16750 2
< 0.1%
-14674.49 1
< 0.1%
-13562 1
< 0.1%
-11651 1
< 0.1%
ValueCountFrequency (%)
97106933.19 1
< 0.1%
73982622 1
< 0.1%
62482622 1
< 0.1%
54000000 1
< 0.1%
52419751 1
< 0.1%
44072001 1
< 0.1%
40649810 1
< 0.1%
39500000 1
< 0.1%
28420574 1
< 0.1%
16145096 1
< 0.1%

Family Title
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size237.8 KiB
Office machines and their supplies and accessories
16479 
Computer services
13946 

Length

Max length50
Median length50
Mean length34.873689
Min length17

Characters and Unicode

Total characters1061032
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowComputer services
2nd rowComputer services
3rd rowComputer services
4th rowComputer services
5th rowComputer services

Common Values

ValueCountFrequency (%)
Office machines and their supplies and accessories 16479
54.2%
Computer services 13946
45.8%

Length

2023-05-30T12:16:55.263228image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-05-30T12:16:55.403820image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
and 32958
23.0%
office 16479
11.5%
machines 16479
11.5%
their 16479
11.5%
supplies 16479
11.5%
accessories 16479
11.5%
computer 13946
9.7%
services 13946
9.7%

Most occurring characters

ValueCountFrequency (%)
e 140712
13.3%
s 126766
11.9%
112820
10.6%
i 96341
 
9.1%
c 79862
 
7.5%
a 65916
 
6.2%
r 60850
 
5.7%
n 49437
 
4.7%
p 46904
 
4.4%
h 32958
 
3.1%
Other values (10) 248466
23.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 917787
86.5%
Space Separator 112820
 
10.6%
Uppercase Letter 30425
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 140712
15.3%
s 126766
13.8%
i 96341
10.5%
c 79862
8.7%
a 65916
 
7.2%
r 60850
 
6.6%
n 49437
 
5.4%
p 46904
 
5.1%
h 32958
 
3.6%
f 32958
 
3.6%
Other values (7) 185083
20.2%
Uppercase Letter
ValueCountFrequency (%)
O 16479
54.2%
C 13946
45.8%
Space Separator
ValueCountFrequency (%)
112820
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 948212
89.4%
Common 112820
 
10.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 140712
14.8%
s 126766
13.4%
i 96341
10.2%
c 79862
 
8.4%
a 65916
 
7.0%
r 60850
 
6.4%
n 49437
 
5.2%
p 46904
 
4.9%
h 32958
 
3.5%
f 32958
 
3.5%
Other values (9) 215508
22.7%
Common
ValueCountFrequency (%)
112820
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1061032
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 140712
13.3%
s 126766
11.9%
112820
10.6%
i 96341
 
9.1%
c 79862
 
7.5%
a 65916
 
6.2%
r 60850
 
5.7%
n 49437
 
4.7%
p 46904
 
4.4%
h 32958
 
3.1%
Other values (10) 248466
23.4%

Interactions

2023-05-30T12:15:41.912307image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:08:37.207334image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:09:44.778991image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:13:25.683077image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:14:33.600662image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:15:42.068520image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:08:37.406218image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:10:15.360821image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:13:25.854947image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:14:33.772532image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:16:49.570041image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:09:44.310079image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:11:53.727593image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:14:33.192575image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:15:41.506184image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:16:49.695049image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:09:44.450065image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:12:24.366854image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:14:33.333168image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:15:41.631155image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:16:49.835640image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:09:44.593665image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:12:55.413441image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:14:33.473763image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-05-30T12:15:41.771747image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-05-30T12:16:55.513171image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
PO IdentifierVendor NumberUnit PriceTotal PO ValueTotal PO Value Local CurrencyFamily Title
PO Identifier1.000-0.005-0.003-0.009-0.0090.117
Vendor Number-0.0051.000-0.005-0.002-0.0020.085
Unit Price-0.003-0.0051.0000.8490.8490.019
Total PO Value-0.009-0.0020.8491.0001.0000.019
Total PO Value Local Currency-0.009-0.0020.8491.0001.0000.019
Family Title0.1170.0850.0190.0190.0191.000

Missing values

2023-05-30T12:16:50.069956image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-05-30T12:16:50.413628image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-05-30T12:16:50.757297image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

PO IdentifierVendor NumberVendor NamePO NumberPO ApproverPO Order DatePO Approval DateItemDescriptionUnit PriceTotal PO ValueLocal CurrencyTotal PO Value Local CurrencyFamily Title
07681142981.0ExLibrisP1410545Denise Rivers2012-02-082012-02-28ILS Software MaintenanceSoftware maintenance on Aleph ILS and Catalog Enrichment.72329.2972329.29SGD72329.29Computer services
176958066.0ExLibrisP1410550Denise Rivers2012-02-082012-02-28ILS Software MaintenanceSoftware maintenance on Aleph ILS and catalog enrichment.152389.00152389.00SGD152389.00Computer services
2104671002161.0Alliant Insurance Services, Inc4500219360Denise Rivers2015-06-192015-07-09Insurance Extended WarrantyInsurance Extended Warranty82789.7982789.79SGD82789.79Computer services
31047418030.0Alliant Insurance Services, Inc4500219357Denise Rivers2015-06-202015-07-10Insurance Extended WarrantyInsurance Extended Warranty153308.22153308.22SGD153308.22Computer services
4124591065902.0EMC4500147774Denise Rivers2014-09-112014-10-01Brocade DCX switches, maintenance, migration, and installation services and suppBrocade DCX switches, maintenance, migration, and installation services\nand support.180631.24180631.24SGD180631.24Computer services
51246038794.0EMC4500146103Denise Rivers2014-09-152014-10-05Brocade DCX switches, maintenance, migration, and installation services and suppBrocade DCX switches, maintenance, migration, and installation services\nand supp69430.0069430.00SGD69430.00Computer services
610681763613.0Plug Inn Go, Inc4500166573Michael Johnson2012-09-302012-10-06Appliance Policy Server Software SupportSWG M86 5080 Appliance Policy Server ARS166.67500.01SGD500.01Computer services
7106917224.0Plug Inn Go, Inc4500166574Michael Johnson2012-09-262012-10-06Appliance Policy Server Software SupportSWG M86 5080 Appliance Policy Server ARS166.67500.01SGD500.01Computer services
824021743406.0Smile Business Products, Inc4500218572Michael Johnson2013-03-012013-03-11MX-FR23U - Data Security Kit (hard drive data encryption)MX-FR23U - Data Security Kit (hard drive data encryption)252.76252.76SGD252.76Office machines and their supplies and accessories
9240310803.0Smile Business Products, Inc4500218573Michael Johnson2013-03-022013-04-11MX-FR23U - Data Security Kit (hard drive data encryption)MX-FR23U - Data Security Kit (hard drive data encryption)252.76252.76SGD252.76Office machines and their supplies and accessories
PO IdentifierVendor NumberVendor NamePO NumberPO ApproverPO Order DatePO Approval DateItemDescriptionUnit PriceTotal PO ValueLocal CurrencyTotal PO Value Local CurrencyFamily Title
304153041612214.0Technology Integration GroupGP120082Derrick LewisNaTNaTSAMSUNG MLT-D205-CAS TONER, BLKSAMSUNG MLT-D205-CAS TONER, BLK172.498279.52SGD8279.52Office machines and their supplies and accessories
304163041746690.0Midtown Stationers12-03-0740Bailey ElliottNaTNaTTonerToner1276.201276.20SGD1276.20Office machines and their supplies and accessories
30417304181000618.0Pacific Copier & ComputerIN120018Rachel Martin2021-06-062021-06-06tonerlot5727.505727.50SGD5727.50Office machines and their supplies and accessories
30418304191000633.0Technology Integration Group2PA2H109Anthony DayNaTNaTAssorted HP Toner CartridgeAssorted HP Toner Cartridge319.54319.54SGD319.54Office machines and their supplies and accessories
30419304201743406.0Technology Integration Group4500198630Evan Lyons2015-05-032015-05-03HP Toner Genuine Blk 1.6K Smart Print ctgHP Toner Genuine Blk 1.6K Smart Print ctg98.01588.06SGD588.06Office machines and their supplies and accessories
30420304211000633.0Technology Integration Group1PA2L029 & 30Louis LongNaTNaT4y NB Exchange Warranty4y NB Exchange Warranty57.75115.50SGD115.50Computer services
304213042256613.0Capital Datacorp3167436James LewisNaTNaTsoftware maintenancesoftware maintenance14991.5914991.59SGD14991.59Computer services
304223042317520.0THE PRIMARY SOURCECD0062812Rhonda SandersNaTNaTHP #91 Maintenance Ctg, Design Jet Z6100psHP #91 Maintenance Ctg, Design Jet Z6100ps #HEWC9518A74.0074.00SGD74.00Office machines and their supplies and accessories
304233042456613.0AT&T30-62-016Mrs. Jennifer HaynesNaTNaT2 Port 3rd Gen Multiflex Trunk Voice/Wan int CardNetwork Maintenance1100.001100.00SGD1100.00Computer services
30424304252472.0Enterprise Networking Solutions, Inc4500206683Brittany Hansen MDNaTNaTZerto ReplicationZerto Replication maintenance, software, and consulting services.48660.3048660.30SGD48660.30Computer services